5 Essential Data Science Projects for Your Portfolio

In this video I walk through the 5 essential data science projects that you should have in your portfolio. Having these 5 different projects will show employers that you have diversity in your data science skillset.

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Project 1: Exploratory data analysis (EDA) - This shows that you can clearly tell a story with your data. It also shows that you can collect, clean, and perform feature engineering. I recommend scraping your data or collecting it from an open api.

Project 2: Classification problem - With these projects you are predicting a binary or categorical outcome. An example would be the titanic dataset where you predict if people would have survived the crash.

Project 3: A regression problem - In these types of analyses, you try to predict a continuous outcome. An example would be predicting how many likes a youtube video would get ;).

Project 4: A clustering problem - With this we use algorithms to understand which data points are related to eachother.

Project 5: An advanced topic (NLP, Computer Vision, Deep Neural Nets) - These projects allow you to specialize and show off your skills!

0:00 Intro
0:58 Exploratory Data Analysis
1:28 Classification Project
2:58 Regression Project
3:45 Clustering Project
5:05 Advanced Techniques
6:00 How to win GTC Tickets

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[KenJee_ds]

Thanks for watching everyone! Remember to comment below with the session you would be most interested in attending for your chance to win one of the 3 free tickets to the NVIDIA GTC!

Try watching these videos next!

[ismailcemozcelik]

It was a very eye-opening content for me. When I look back at the past, I remembered that I was already doing some projects, but I also saw that I did not think deeply while I was doing any of them. For example, when I was estimating house price, I realized that, as you said, I didn't give much thought to how much influence the links between different data points have on the price of a house. But data science is a journey and some fails can be seen like flowers around the road LoL :))

[adriansrfr]

You're breakdown in the description is extremely helpful. The only thing that could make the vid better would be to give visual examples during the discussion. Thanks!

[TinaHuang]

Amazing amazing suggestions!! I would also love to attend the deep learning ones!

[Graenelolz]

I just halfassed my way through my Master‘s and want to seriously pursue Data Science again. Your videos are both so insightful and encouraging I can‘t thank you enough. Thanks man, really.

[habiburrehman]

Your channel is a lot of help in data-science related stuff. I'm glad I found it and I recommend it to people... Thanks a lot for your informative videos.

[filmzone]

Thanks for the video !! super helpful!! and love the sport examples !

[tomorrow]

Thank you for this video. I recently started in DS and i've been seeking for projects to build a portfolio.

[anglinabhambra]

I would most look forward to: GeoCOV: Toward Real-time Analytics and Cartography for Covid Geospatial Data with Machine Learning Algorithms [A22048]

Admittedly I haven't been able to browse all 337 scheduled sessions, but this one resonates with me as I'm finishing up a 9month internship this coming week where I have been learning a lot about spatial data.

Whilst I'm commenting - Thank you very much for all of your awesome videos! I rarely see people walking through the business side to their projects - your videos have been very helpful :D

[donnelly]

Very intriguing! When you got to the golfing section, it gives me hope that once I get my master's in data science I will actually be able to combine data science with exercise science. My master's in exercise science may not be so useless after all!

[TyliteTony]

wow!!! I was here when u were at 30k. Your channel grew so fast!!!!
Great work.

[DataProfessor]

Thanks for another great video Ken! Definitely a must watch video for all aspiring data scientists wanting to break into the field. 😃

[santoshthapa]

I am just loving your content man.... You are a great inspiration for me... Thankyou

[adi-larrazolo]

Absolutely love your content! It's so helpful :)

[aamnasuhail]

Whenever I feel like questioning my decision to learn Datascience I came back to your videos.
I don't know if it's progress but I now know roughly whatever projects you're talking in this video. That what kind of projects they actually are. So, maybe it is actually progress. Fingers crossed 🤞🤞

[shishaa_here]

I have been looking for this kind of video for long. Thank you

[AndrewMoMoney]

A sneaky Saturday upload! In your POV, how does someone know they're ready to progress from a regression/classification problem to a more advanced method?

[larigiba]

The ABC of Data Science Projects:

-Analysis
-Build something advanced
-Classification
-Clustering
-Regression

I know I might have cheated a tiny bit with the second entry and regression might have slipped of just a tiny bit of the "ABC"-edge but outliers are common in DS anyway so it's a perfect, scientifically proven analogy (fact).

[anvy]

Thanks for brokering these tickets Ken. Would be super keen to attend the NVIDIA Inception Premier Showcase - The Top AI Startups in North America session.

[RaisulIslam]

It would really help me if I can attend the Instructor Led Workshop " Fundamentals of Deep Learning " . I've been training myself for quiet some time on Deep Learning and Machine Learning Model Developments. Also I am a Applied Statistics student so not much of a CS background. I think, attending this conference would really boost up my understanding of the sectors and motivate me for a further journey.

P.S: Love your channel, keep doing what you're doing. All the best.